Looking Into the Future for Agriculture and AKST | 315
to-slaughtered animals from FAOSTAT for 1999-2001 the same base that was used for the IMPACT simulations. To es-
timate changes in grazing intensity, the extent of each system type within each FPU was estimated, and livestock numbers
within each FPU were allocated to each system within the FPU on a pro-rata basis. Existing global ruminant livestock
distribution maps for current conditions were used as a basis for the future variants, to derive the livestock allocation pro-
portions appropriate to each system within each FPU. The eleven livestock systems in the Seré and Steinfeld
classiication were aggregated to three: rangeland systems, mixed systems rainfed and irrigated, and “other” systems.
These “other” systems include the intensive landless sys- tems, both monogastric pigs and poultry and ruminant.
5.3.2.6 Trade
Trade conditions seen today are presumed to continue out to 2050. No trade liberalization or reduction in sectoral
protection is assumed for the reference world.
5.3.2.7 Water
Projections for water requirements, infrastructure capacity expansion, and water use eficiency improvement are con-
ducted by IMPACT-WATER. These projections are com- bined with the simulated hydrology to estimate water use
and consumption through water system simulation by IM- PACT-WATER Rosegrant et al., 2002. “Normal” priority
has been given to all sectors, with irrigation being the low- est, compared with domestic, industrial and livestock uses.
The hydrology module of the IMPACT-WATER global food and water model derives effective precipitation, poten-
tial and actual evapotranspiration and runoff at these 0.5 degree pixels and scale them up to the level of FPUs, which
Growth in SSA has been low in the recent past, but there is much room for recovery, which will lead to strong,
if modest growth. All of SSA should see an average of 3.9 growth out to 2050. Central and Western SSA will see fairly
stable to slightly increasing growth with most countries ex- periencing annual growth in the 5-6 range. The remain-
der of SSA will see strong increases in GDP growth rates as recovery continues. Though many countries in East and
Southern SSA will be experiencing growth less than 4 out to 2025, all of these countries are projected to see growth
rates reach 6 to 9 by 2050.
5.3.2.5 Livestock
The reference run was implemented in the following way: First, global livestock systems were mapped for the baseline
year 2000 and for the reference run for 2030 and 2050, using the reference populations and General Circulation
Model GCM scenarios for these years. The latter was used to generate surfaces of length of growing period number
of days per year to 2030 and 2050. In the absence of GCM output for diurnal temperature variation and maximum or
minimum temperatures, average monthly diurnal tempera- ture variation was estimated using a crude relationship in-
volving average 24 hour daily temperature and the average day-time temperature. The 0.5° latitude-longitude grid size
of the GCM data was downscaled to 10 arc-minutes 0.17° latitude-longitude, and characteristic daily weather data for
the monthly climate normal for the reference run in 2030 and 2050 were generated using the methods of Jones and
Thornton 2003. For the second part of the analysis, the livestock numbers that were generated as output from the
IMPACT model at the resolution of the FPUs were converted to live-animal equivalents using country-level ratios of live-
Table 5-2.
Population growth. 2000-05
2005-10 2010-15
2015-20 2020-25
2025-30 2030-35
2035-40 2040-45
2045-50 NAE
0.3 0.3
0.2 0.2
0.1 0.1
0.0 0.0
0.0 -0.1
CWANA 2.0
1.9 1.8
1.7 1.5
1.3 1.2
1.0 0.9
0.8 LAC
1.4 1.3
1.2 1.0
0.9 0.7
0.6 0.5
0.3 0.2
SSA 2.3
2.2 2.2
2.1 2.0
1.9 1.7
1.6 1.5
1.4 ESAP
1.1 1.0
0.9 0.8
0.6 0.5
0.4 0.3
0.2 0.1
Source: UN, 2005.
Table 5-3.
Per capita income growth. Region
2000-05 2005-10
2010-15 2015-20
2020-25 2025-30
2030-35 2035-40
2040-45 2045-50
NAE 3.3
2.2 2.8
2.8 2.7
2.5 2.3
2.0 1.8
1.7 CWANA
4.3 3.6
3.7 3.6
3.5 3.8
4.1 4.5
4.8 5.0
LAC 4.3
1.1 3.7
4.6 4.4
4.4 4.5
4.6 4.6
4.5 SSA
3.6 3.4
4.2 4.3
4.4 4.6
4.9 5.1
5.2 5.2
ESAP 3.2
2.7 3.7
3.8 3.6
3.7 3.7
3.8 3.8
3.7
Source: Authors based on MEA 2005.
316 | IAASTD Global Report
5.3.3 Description of reference world outcomes 5.3.3.1 Food sector
Food supply and demand. In the reference run, global food production increases 1.2 per year during 2000-2050.
This growth is a result of rapid economic growth, slowing population growth, and increased diversiication of diets.
Growth of demand for cereals slows during 2000-2025 and again from 2025-2050, from 1.4 per year to 0.7 per
year. Demand for meat products beef, sheep, goat, pork, poultry grows more rapidly, but also slows somewhat after
2025, from 1.8 per year to 0.9 annually. Changes in cereal and meat consumption per capita vary
signiicantly among IAASTD regions Figures 5-2 and 5-3. Over the projection period, per capita demand for cereals
as food declines in the LAC region and in the ESAP region. On the other hand demand is projected to considerably in-
crease in the sub-Saharan Africa region and also increase in the NAE and CWANA regions. Recovery and strengthen-
ing of economic growth in sub-Saharan Africa will drive relatively fast growth in regional demand for food. In de-
veloping countries and particularly Asia, rising incomes and rapid urbanization will change the composition of cereal
demand. Per capita food consumption of maize and coarse grains will decline as consumers shift to wheat and rice. As
incomes rise further and lifestyles change with urbaniza- tion, there will be a secondary shift from rice to wheat. In
the SSA region, growing incomes are expected to lead to a shift from roots and tubers to rice and wheat. Per capita
food demand for roots and tubers in SSA is projected to de- cline from 171 kg to 137 kg between 2000 and 2050, while
rice and wheat demand are expected to grow from 18-20 kg to 30-33 kg Table 5-4. Under the reference run, the
composition of food demand growth across commodities is expected to change considerably. Total cereal demand is
projected to grow by 1,305 million tonnes, or by 70; 50 of the increase is expected for maize; 23 for wheat; 10
for rice; and the reminder, for sorghum and other coarse grains.
Demand for meat products continues to grow rapidly across all six IAASTD regions, by 6-23 kilograms per per-
son. The increase is fastest in the LAC and ESAP regions and slowest in the SSA and NAE regions. Rapid growth in meat
and milk demand in most of the developing world will put strong demand pressure on maize and other coarse grains
as feed. Globally, cereal demand as feed increases by 553 million tonnes during 2000-2050, a staggering 42 of total
cereal demand increase Figure 5-4. Tables 5-5, 5-6, 5-7 and 5-8 present results for changes
in livestock numbers for beef, sheep and goats, pigs, and poultry, respectively, for the IAASTD regions. The global
population of bovines is projected to increase from some 1.5 billion animals in 2000 to 2.6 billion in 2050 in the refer-
ence run. Substantial increases are projected to occur in all regions except NAE: the number of bovines is projected to
double in CWANA and ESAP, and to increase by 50 in SSA, for example. Cattle numbers are projected to peak in
SSA in about 2045. Bovine populations are relatively stable in NAE to 2050 in the reference run.
Similar patterns are seen for changes in sheep and goat populations. The global population is expected to increase
are also used for some of the other analyses, in the spatial operational unit of IMPACT-WATER. Projections for water
requirements, infrastructure capacity expansion, and water use eficiency improvement are conducted by IMPACT-WATER.
These projections are combined with the simulated hydrology to estimate water use and consumption through water system
simulation by IMPACT-WATER Rosegrant et al., 2002.
5.3.2.7 Energy use and production
As discussed in Chapter 4, the energy sector may develop in very different ways. For the reference projection, we have
chosen to loosely couple future outcomes to IEA reference scenario—a scenario that lies central in the range of avail-
able energy projections. The policy variant has been devel- oped using the IMAGETIMER model and incorporates
the speciic assumptions of the IAASTD reference projec- tion with respect to economic growth and land use change.
In terms of energy demand growth the IEA scenario is a mid-range scenario compared to full range of scenarios pub-
lished in literature. For the development of the energy mix, it is a conventional development scenario assuming no ma-
jor changes in existing energy policies andor societal prefer- ences. These assumptions are also included in the IAASTD
reference projection.
5.3.2.8 Climate change
Climate change is both driving different outcomes of key variables of the reference run like crop productivity and
water availability and is an outcome of the agricultural projections of the reference run, through land-use changes
and agricultural emissions, mainly from the livestock sec- tor FAO, 2006b. Given the medium energy outcomes in
the reference run see 5.3.3.3, results from the B2 scenario are directly used in most of the modeling tools. From the
available B2 scenario, the ensemble mean of the results of the HadCM3 model for B2 scenario was used. The pattern
scaling method applied was that of the Climate Research Unit, University of East Anglia. The “SRES B2 HadCM3”
climate scenario is a transient scenario depicting gradually evolving global climate from 2000 through 2100. In the IM-
AGE model, climate change is an output of the model. The IMAGE model uses a global climate model MAGICC to
calculate global mean temperature change—and uses down- scaling techniques to downscale this data to a 0.5 x 0.5 grid.
Through this approach, different GCM results can be used to assess the consequences of the uncertainty in local cli-
mate change. For the reference run, the pattern of Hadley Centre’s HadCM2 is used for the downscaling approach,
which is consistent with the pattern used in the other model- ing tools. For the simulations of the reference world, the me-
dium climate sensitivity value is used of the Third Assessment Report 2.5°C, which has been adjusted slightly in the latest
IPCC report. According to IPCC, the climate sensitivity is likely to be in the range of 2 to 4.5°C with a best estimate of
about 3°C, and is very unlikely to be less than 1.5°C IPCC, 2007. Climate sensitivity is not a projection but is deined as
the global average surface warming following a doubling of carbon dioxide concentrations IPCC, 2007. The uncertain-
ties in the climate sensitivity are not assessed in the reference world. Speciic sensitivity analyses will show the importance
of the uncertainties in values of the climate sensitivity.
